Instructions to use darask0/anima-distill-loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use darask0/anima-distill-loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("circlestone-labs/Anima", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("darask0/anima-distill-loras") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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## ソースコード
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訓練コード・データセット生成・Modal 実装一式:
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[**darask0/rapid-anima**](https://huggingface.co/darask0/rapid-anima)
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## File Formats
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## ソースコード
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訓練コード・データセット生成・Modal 実装一式:
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- HF (同アカウント上): [**darask0/rapid-anima**](https://huggingface.co/darask0/rapid-anima)
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- GitHub: [**daraskme/rapid-anima**](https://github.com/daraskme/rapid-anima)
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両 repo は同内容のミラー。Issue / PR は GitHub 側で対応推奨。
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## File Formats
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